The present invention relates to data integration. In one aspect, data integration can be viewed as taking a dataset specified according to one format, and combining it with data that has a different format, while still preserving the meaning of the data. For example, in one dataset, a date of birth may be specified by separate fields for a month, day and year of birth. In another dataset, the date of birth may simply be specified by a single date field. In the datasets, there may be relations to an object class to which the date of birth applies. That object class may in turn have relations to still other classes. For example, a dataset could comprise all the information concerning an account profile and trading history for a number of clients in a brokerage firm. Such account profile would include various biographical information, and a potentially large amount of data on stock trades, which may have been stored in a relational database specific to that brokerage. If one would want to convert that data to a different format, such as to integrate two brokerages, conventionally, a database integrator would determine an appropriate mapping between the formats of the datasets and then have a machine perform the translations.
However, the above is an example of a relatively confined problem statement, with a specific and non-reoccurring business need to translate a relatively defined set of data (i.e., the amount of data may be large, but the nature and the contents of the dataset are well-specified). There are many other areas where these circumstances do not necessarily exist. As such, there is continued interest in research related to these kinds of problems.